Treffer: Tellurium-Vacancy Engineering in Ultrathin Bi 2 Te 3 Enables Broadband Multifunctional Optoelectronic Synapse for Energy-Efficient Neuromorphic and Optical Information Processing.
Title:
Tellurium-Vacancy Engineering in Ultrathin Bi 2 Te 3 Enables Broadband Multifunctional Optoelectronic Synapse for Energy-Efficient Neuromorphic and Optical Information Processing.
Authors:
Nandi S; Department of Physics, Indian Institute of Technology Guwahati, Guwahati, India., Ghosal S; Department of Physics, Indian Institute of Technology Guwahati, Guwahati, India., Choudhary G; Department of Physics, Indian Institute of Technology Guwahati, Guwahati, India., Roy SS; Department of Physics, Indian Institute of Technology Guwahati, Guwahati, India., Meyyappan M; Centre for Nanotechnology, Indian Institute of Technology Guwahati, Guwahati, India., Giri PK; Department of Physics, Indian Institute of Technology Guwahati, Guwahati, India.; Centre for Nanotechnology, Indian Institute of Technology Guwahati, Guwahati, India.
Source:
Small (Weinheim an der Bergstrasse, Germany) [Small] 2026 Jan 23, pp. e11836. Date of Electronic Publication: 2026 Jan 23.
Publication Model:
Ahead of Print
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Wiley-VCH Country of Publication: Germany NLM ID: 101235338 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1613-6829 (Electronic) Linking ISSN: 16136810 NLM ISO Abbreviation: Small Subsets: MEDLINE
Imprint Name(s):
Original Publication: Weinheim, Germany : Wiley-VCH, c2005-
References:
K. He, Y. Liu, J. Yu, et al., “Artificial Neural Pathway Based on a Memristor Synapse for Optically Mediated Motion Learning,” ACS Nano 16, no. 6 (2022): 9691–9700, https://doi.org/10.1021/acsnano.2c03100.
H. Haick and N. Tang, “Artificial Intelligence in Medical Sensors for Clinical Decisions,” ACS Nano 15, no. 3 (2021): 3557–3567, https://doi.org/10.1021/acsnano.1c00085.
L. Mennel, J. Symonowicz, S. Wachter, D. K. Polyushkin, A. J. Molina‐Mendoza, and T. Mueller, “Ultrafast Machine Vision With 2D Material Neural Network Image Sensors,” Nature 579, no. 7797 (2020): 62–66, https://doi.org/10.1038/s41586‐020‐2038‐x.
P. A. Merolla, J. V. Arthur, R. Alvarez‐icaza, et al., “A Million Spiking‐Neuron Integrated Circuit With a Scalable Communication Network and Interface,” Science 345, no. 6197 (2014): 668–673, https://doi.org/10.1126/science.1254642.
S. Dai, Y. Zhao, Y. Wang, et al., “Recent Advances in Transistor‐Based Artificial Synapses,” Advanced Functional Materials 29, no. 42 (2019): 1903700, https://doi.org/10.1002/adfm.201903700.
R. Jana, S. Ghosh, R. Bhunia, and A. Chowdhury, “Recent Developments in the State‐of‐the‐Art Optoelectronic Synaptic Devices Based on 2D Materials: A Review,” Journal of Materials Chemistry C 12, no. 15 (2024): 5299–5338, https://doi.org/10.1039/d4tc00371c.
Q. Wu, J. Wang, J. Cao, et al., “Photoelectric Plasticity in Oxide Thin Film Transistors With Tunable Synaptic Functions,” Advanced Electronic Materials 4, no. 12 (2018): 1800556, https://doi.org/10.1002/aelm.201800556.
G. Li, D. Xie, H. Zhong, et al., “Photo‐Induced Non‐Volatile VO2 Phase Transition for Neuromorphic Ultraviolet Sensors,” Nature Communication 13, no. 1 (2022): 1729, https://doi.org/10.1038/s41467‐022‐29456‐5.
H. Tan, Z. Ni, W. Peng, et al., “Broadband Optoelectronic Synaptic Devices Based on Silicon Nanocrystals for Neuromorphic Computing,” Nano Energy 52 (2018): 422–430, https://doi.org/10.1016/j.nanoen.2018.08.018.
S. Mukherjee, D. Dutta, A. Ghosh, and E. Koren, “Graphene‐In2Se3 van Der Waals Heterojunction Neuristor for Optical In‐Memory Bimodal Operation,” ACS Nano 17, no. 22 (2023): 22287–22298, https://doi.org/10.1021/acsnano.3c03820.
Z. D. Luo, X. Xia, M. M. Yang, N. R. Wilson, A. Gruverman, and M. Alexe, “Artificial Optoelectronic Synapses Based on Ferroelectric Field‐Effect Enabled 2D Transition Metal Dichalcogenide Memristive Transistors,” ACS Nano 14, no. 1 (2020): 746–754, https://doi.org/10.1021/acsnano.9b07687.
X. Ren, X. He, X. Li, et al., “An Optical Artificial Synapse Based on Single‐Crystal Se‐Vacancy Bi2 O2 Se,” Advanced Optical Materials 12, no. 14 (2024): 2302852, https://doi.org/10.1002/adom.202302852.
H. Chen, N. Qin, Z. Ren, et al., “MXene‐Based Optoelectronic Synaptic Transistors Utilize Attentional Mechanisms to Achieve Hierarchical Responses,” Journal of Materials Chemistry C 12, no. 20 (2024): 7197–7205, https://doi.org/10.1039/d4tc00473f.
W. Xiao, L. Shan, H. Zhang, et al., “High Photosensitivity Light‐Controlled Planar ZnO Artificial Synapse for Neuromorphic Computing,” Nanoscale 13, no. 4 (2021): 2502–2510, https://doi.org/10.1039/d0nr08082a.
R. Li, Y. Dong, F. Qian, et al., “CsPbBr3/Graphene Nanowall Artificial Optoelectronic Synapses for Controllable Perceptual Learning,” PhotoniX 4 (2023): 4, https://doi.org/10.1186/s43074‐023‐00082‐8.
P. Guo, J. Zhang, D. Liu, et al., “Optoelectronic Synaptic Transistors Based on Solution‐Processable Organic Semiconductors and CsPbCl3 Quantum Dots for Visual Nociceptor Simulation and Neuromorphic Computing,” ACS Applied Materials & Interfaces 15, no. 44 (2023): 51483–51491, https://doi.org/10.1021/acsami.3c09355.
H. Yang, Y. Hu, X. Zhang, et al., “Near‐Infrared Optical Synapses Based on Multilayer MoSe2 Moiré Superlattice for Artificial Retina,” Advanced Functional Materials 34, no. 2 (2024): 2308149, https://doi.org/10.1002/adfm.202308149.
S. Wang, X. Hou, L. Liu, et al., “A Photoelectric‐Stimulated MoS2 Transistor for Neuromorphic Engineering,” Research 2019 (2019): 1618798, https://doi.org/10.34133/2019/1618798.
Z. Guo, J. Liu, X. Han, et al., “High‐Performance Artificial Synapse Based on CVD‐Grown WSe2 Flakes With Intrinsic Defects,” ACS Applied Materials & Interfaces 15, no. 15 (2023): 19152–19162, https://doi.org/10.1021/acsami.3c00417.
Y. Chen, Y. Huang, J. Zeng, et al., “Energy‐Efficient ReS2‐Based Optoelectronic Synapse for 3D Object Reconstruction and Recognition,” ACS Applied Materials & Interfaces 15, no. 50 (2023): 58631–58642, https://doi.org/10.1021/acsami.3c14958.
M. Huang, W. Ali, L. Yang, et al., “Multifunctional Optoelectronic Synapses Based on Arrayed MoS2 Monolayers Emulating Human Association Memory,” Advanced Science 10, no. 16 (2023): 2300120, https://doi.org/10.1002/advs.202300120.
A. Sharma, T. D. Senguttuvan, V. N. Ojha, and S. Husale, “Novel Synthesis of Topological Insulator Based Nanostructures (Bi2 Te3) Demonstrating High Performance Photodetection,” Sci Rep 9, no. 1 (2019): 1–8, https://doi.org/10.1038/s41598‐019‐40394‐z.
W. Wu, W. He, D. Ling, et al., “Enhanced Self‐Powered Photoresponse of a Bi2 Te3 ‐Based Vertical Heterojunction Broadband Photodetector by Carrier Blocking Layer Engineering,” Small 21, no. 29 (2025): 2501484, https://doi.org/10.1002/smll.202501484.
S. Nandi, S. Ghosal, M. Meyyappan, and P. K. Giri, “Defect‐Engineered 2D Bi2Se3‐Based Broadband Optoelectronic Synapses With Ultralow Energy Consumption for Neuromorphic Computing,” Materials Horizons 12, no. 12 (2025): 4274–4288, https://doi.org/10.1039/d4mh01625d.
X. Qi, J. Zhang, J. Cai, X. Chu, X. Shao, and Z. L. Hou, “Delicate Construction of Bi2Te3 Nanosheets for Striking Artificial Synapses and Broadband Photodetecting,” Journal of Alloys and Compounds 1002 (2024): 175350, https://doi.org/10.1016/j.jallcom.2024.175350.
Z. Wan, Q. Zhang, F. Hu, et al., “Topological Insulator Optoelectronic Synapses for High‐Accuracy Binary Image Recognition using Recurrent Neural Networks,” Advanced Optical Materials 11, no. 2 (2023): 2201852, https://doi.org/10.1002/adom.202201852.
Y. Zhang, Q. You, W. Huang, et al., “Few‐Layer Hexagonal Bismuth Telluride (Bi2Te3) Nanoplates With High‐Performance UV–vis Photodetection,” Nanoscale Advances 2, no. 3 (2020): 1333–1339, https://doi.org/10.1039/d0na00006j.
C. Lu, M. Luo, W. Dong, et al., “Bi2 Te3 /Bi2 Se3 /Bi2 S3 Cascade Heterostructure for Fast‐Response and High‐Photoresponsivity Photodetector and High‐Efficiency Water Splitting With a Small Bias Voltage,” Advanced Science 10, no. 6 (2023): 2205460, https://doi.org/10.1002/advs.202205460.
Y. Zhang, W. He, D. Wang, et al., “High‐Performance Self‐Powered UV‐to‐NIR Imaging Photodetector Based on Bi2Te3 p‐n Homojunction,” Materials Today Physics 56 (2025): 101779, https://doi.org/10.1016/j.mtphys.2025.101779.
G. Wang, Q. Li, W. Zhang, et al., “Unveiling the Synergy of Architecture and Anion Vacancy on Bi2 Te3– x @NPCNFs for Fast and Stable Potassium Ion Storage,” ACS Applied Materials & Interfaces 16, no. 11 (2024): 13858–13868, https://doi.org/10.1021/acsami.4c00248.
S. Hu, X. Huang, L. Zhang, et al., “Vacancy‐Defect Topological Insulators Bi2 Te3−x Embedded in N and B Co‐Doped 1D Carbon Nanorods Using Ionic Liquid Dopants for Kinetics‐Enhanced Li–S Batteries,” Advanced Functional Materials 33, no. 20 (2023): 2214161, https://doi.org/10.1002/adfm.202214161.
C. Wang, X. Zhu, L. Nilsson, et al., “In Situ Raman Spectroscopy of Topological Insulator Bi2Te3 Films With Varying Thickness,” Nano Research 6, no. 9 (2013): 688–692, https://doi.org/10.1007/s12274‐013‐0344‐4.
V. Chis, I. Y. Sklyadneva, K. A. Kokh, V. A. Volodin, O. E. Tereshchenko, and E. V. Chulkov, “Vibrations in Binary and Ternary Topological Insulators: First‐Principles Calculations and Raman Spectroscopy Measurements,” Physical Review B—Condensed Matter Material Physics 86, no. 17 (2012): 1–12, https://doi.org/10.1103/PhysRevB.86.174304.
G. Ye, Y. Gong, J. Lin, et al., “Defects Engineered Monolayer MoS2 for Improved Hydrogen Evolution Reaction,” Nano Letters 16, no. 2 (2016): 1097–1103, https://doi.org/10.1021/acs.nanolett.5b04331.
K. Jeong, D. Park, I. Maeng, et al., “Modulation of Optoelectronic Properties of the Bi2Te3 Nanowire by Controlling the Formation of Selective Surface Oxidation,” Appl Surf Sci 548 (2021): 149069, https://doi.org/10.1016/j.apsusc.2021.149069.
R. Galceran, F. Bonell, L. Camosi, et al., “Passivation of Bi2 Te3 Topological Insulator by Transferred CVD‐Graphene: Toward Intermixing‐Free Interfaces,” Advanced Materials Interfaces 9, no. 36 (2022): 2201997, https://doi.org/10.1002/admi.202201997.
A. G. Shard, “Practical Guides for X‐Ray Photoelectron Spectroscopy: Quantitative XPS,” Journal of Vacuum Science & Technology A 38, no. 4 (2020): 41201, https://doi.org/10.1116/1.5141395.
J. F. Moulder, W. F. Stickle, W. M. Sobol, and K. D. Bomben Handbook of X‐Ray Photoelectron Spectroscopy, Physical Electronics Division, Perkin‐Elmer Corporation, Eden Prairie, MN, USA, (1992).
L. Giri, G. Mallick, A. C. Jackson, M. H. Griep, and S. P. Karna, “Synthesis and Characterization of High‐Purity, Single Phase Hexagonal Bi2Te3 Nanostructures,” RSC Advances 5, no. 32 (2015): 24930–24935, https://doi.org/10.1039/c5ra02303c.
R. P. Panmand, G. Kumar, S. M. Mahajan, N. Shroff, B. B. Kale, and S. W. Gosavi, “Growth of Bi2Te3 Quantum Dots/Rods in Glass: A Unique Highly Stable Nanosystem With Novel Functionality for High Performance Magneto Optical Devices,” Physical Chemistry Chemical Physics 14, no. 47 (2012): 16236, https://doi.org/10.1039/c2cp43169f.
B. Sreelakshmi and R. Thamankar, “Investigation of the Transient Photo‐Response and Switching Window of an Al/Indigo/Al Device: Unveiling Negative Photoconductivity and the Photo‐Enhanced Memory Window,” Materials Advance 5, no. 14 (2024): 5912–5921, https://doi.org/10.1039/d4ma00302k.
P. Ci, X. Tian, J. Kang, et al., “Chemical Trends of Deep Levels in Van Der Waals Semiconductors,” Nat Commun 11, no. 1 (2020): 1–8, https://doi.org/10.1038/s41467‐020‐19247‐1.
J. Jiang, C. Ling, T. Xu, et al., “Defect Engineering for Modulating the Trap States in 2D Photoconductors,” Advanced Materials 30, no. 40 (2018): 1804332, https://doi.org/10.1002/adma.201804332.
T. Chen, X. Wang, D. Hao, et al., “Photonic Synapses With Ultra‐Low Energy Consumption Based on Vertical Organic Field‐Effect Transistors,” Advanced Optical Materials 9, no. 8 (2021): 2002030, https://doi.org/10.1002/adom.202002030.
S. E. Ng, J. Yang, R. A. John, and N. Mathews, “Adaptive Latent Inhibition in Associatively Responsive Optoelectronic Synapse,” Advanced Functional Materials 31, no. 28 (2021): 2100807, https://doi.org/10.1002/adfm.202100807.
J. Jiang, W. Xu, Z. Sun, et al., “Wavelength‐Controlled Photoconductance Polarity Switching via Harnessing Defects in Doped PdSe2 for Artificial Synaptic Features,” Small 20, no. 13 (2024): 2306068, https://doi.org/10.1002/smll.202306068.
R. C. Atkinson and R. M. Shiffrin, “Human Memory: A Proposed System and Its Control Processes,” Psychology of Learning and Motivation, Academic Press 2 (1968): 89–195, https://doi.org/10.1016/S0079‐7421(08)60422‐3.
AT&T Laboratories Cambridge ORL Face Database available, https://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html 2009.
P. Zhao, X. Peng, M. Cui, et al., “Multifunctional Two‐Terminal Optoelectronic Synapse Based on an Organic Semiconductor Film,” ACS Applied Polymer Materials 5, no. 10 (2023): 8764–8773, https://doi.org/10.1021/acsapm.3c02012.
M. Cordts, M. Omran, S. Ramos, et al., “The Cityscapes Dataset for Semantic Urban Scene Understanding,” Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit 2016 (2016): 3213–3223, https://doi.org/10.1109/CVPR.2016.350.
J. Wu, W. Liu, C. Li, et al., “A State‐of‐the‐Art Survey of U‐Net in Microscopic Image Analysis: From Simple Usage to Structure Mortification,” Neural Computing and Applications 36, no. 7 (2023): 3317–3346, https://doi.org/10.1007/s00521‐023‐09284‐4.
R. G. Parr, “Density Functional Theory,” Annual Review of Physical Chemistry 34 (1983): 631–656, https://doi.org/10.1146/annurev.pc.34.100183.003215.
P. Giannozzi, S. Baroni, N. Bonini, et al., “QUANTUM ESPRESSO: A Modular and Open‐Source Software Project for Quantum Simulations of Materials,” Journal of Physics: Condensed Matter 21, no. 39 (2009): 395502, https://doi.org/10.1088/0953‐8984/21/39/395502.
P. E. Blöchl, “Projector Augmented‐Wave Method,” Phys Rev B 50, no. 24 (1994): 17953–17979, https://doi.org/10.1103/PhysRevB.50.17953.
J. P. Perdew, K. Burke, and M. Ernzerhof, “Generalized Gradient Approximation Made Simple,” Physical Review Letters 77, no. 18 (1996): 3865–3868, https://doi.org/10.1103/PhysRevLett.77.3865.
H. Haick and N. Tang, “Artificial Intelligence in Medical Sensors for Clinical Decisions,” ACS Nano 15, no. 3 (2021): 3557–3567, https://doi.org/10.1021/acsnano.1c00085.
L. Mennel, J. Symonowicz, S. Wachter, D. K. Polyushkin, A. J. Molina‐Mendoza, and T. Mueller, “Ultrafast Machine Vision With 2D Material Neural Network Image Sensors,” Nature 579, no. 7797 (2020): 62–66, https://doi.org/10.1038/s41586‐020‐2038‐x.
P. A. Merolla, J. V. Arthur, R. Alvarez‐icaza, et al., “A Million Spiking‐Neuron Integrated Circuit With a Scalable Communication Network and Interface,” Science 345, no. 6197 (2014): 668–673, https://doi.org/10.1126/science.1254642.
S. Dai, Y. Zhao, Y. Wang, et al., “Recent Advances in Transistor‐Based Artificial Synapses,” Advanced Functional Materials 29, no. 42 (2019): 1903700, https://doi.org/10.1002/adfm.201903700.
R. Jana, S. Ghosh, R. Bhunia, and A. Chowdhury, “Recent Developments in the State‐of‐the‐Art Optoelectronic Synaptic Devices Based on 2D Materials: A Review,” Journal of Materials Chemistry C 12, no. 15 (2024): 5299–5338, https://doi.org/10.1039/d4tc00371c.
Q. Wu, J. Wang, J. Cao, et al., “Photoelectric Plasticity in Oxide Thin Film Transistors With Tunable Synaptic Functions,” Advanced Electronic Materials 4, no. 12 (2018): 1800556, https://doi.org/10.1002/aelm.201800556.
G. Li, D. Xie, H. Zhong, et al., “Photo‐Induced Non‐Volatile VO2 Phase Transition for Neuromorphic Ultraviolet Sensors,” Nature Communication 13, no. 1 (2022): 1729, https://doi.org/10.1038/s41467‐022‐29456‐5.
H. Tan, Z. Ni, W. Peng, et al., “Broadband Optoelectronic Synaptic Devices Based on Silicon Nanocrystals for Neuromorphic Computing,” Nano Energy 52 (2018): 422–430, https://doi.org/10.1016/j.nanoen.2018.08.018.
S. Mukherjee, D. Dutta, A. Ghosh, and E. Koren, “Graphene‐In2Se3 van Der Waals Heterojunction Neuristor for Optical In‐Memory Bimodal Operation,” ACS Nano 17, no. 22 (2023): 22287–22298, https://doi.org/10.1021/acsnano.3c03820.
Z. D. Luo, X. Xia, M. M. Yang, N. R. Wilson, A. Gruverman, and M. Alexe, “Artificial Optoelectronic Synapses Based on Ferroelectric Field‐Effect Enabled 2D Transition Metal Dichalcogenide Memristive Transistors,” ACS Nano 14, no. 1 (2020): 746–754, https://doi.org/10.1021/acsnano.9b07687.
X. Ren, X. He, X. Li, et al., “An Optical Artificial Synapse Based on Single‐Crystal Se‐Vacancy Bi2 O2 Se,” Advanced Optical Materials 12, no. 14 (2024): 2302852, https://doi.org/10.1002/adom.202302852.
H. Chen, N. Qin, Z. Ren, et al., “MXene‐Based Optoelectronic Synaptic Transistors Utilize Attentional Mechanisms to Achieve Hierarchical Responses,” Journal of Materials Chemistry C 12, no. 20 (2024): 7197–7205, https://doi.org/10.1039/d4tc00473f.
W. Xiao, L. Shan, H. Zhang, et al., “High Photosensitivity Light‐Controlled Planar ZnO Artificial Synapse for Neuromorphic Computing,” Nanoscale 13, no. 4 (2021): 2502–2510, https://doi.org/10.1039/d0nr08082a.
R. Li, Y. Dong, F. Qian, et al., “CsPbBr3/Graphene Nanowall Artificial Optoelectronic Synapses for Controllable Perceptual Learning,” PhotoniX 4 (2023): 4, https://doi.org/10.1186/s43074‐023‐00082‐8.
P. Guo, J. Zhang, D. Liu, et al., “Optoelectronic Synaptic Transistors Based on Solution‐Processable Organic Semiconductors and CsPbCl3 Quantum Dots for Visual Nociceptor Simulation and Neuromorphic Computing,” ACS Applied Materials & Interfaces 15, no. 44 (2023): 51483–51491, https://doi.org/10.1021/acsami.3c09355.
H. Yang, Y. Hu, X. Zhang, et al., “Near‐Infrared Optical Synapses Based on Multilayer MoSe2 Moiré Superlattice for Artificial Retina,” Advanced Functional Materials 34, no. 2 (2024): 2308149, https://doi.org/10.1002/adfm.202308149.
S. Wang, X. Hou, L. Liu, et al., “A Photoelectric‐Stimulated MoS2 Transistor for Neuromorphic Engineering,” Research 2019 (2019): 1618798, https://doi.org/10.34133/2019/1618798.
Z. Guo, J. Liu, X. Han, et al., “High‐Performance Artificial Synapse Based on CVD‐Grown WSe2 Flakes With Intrinsic Defects,” ACS Applied Materials & Interfaces 15, no. 15 (2023): 19152–19162, https://doi.org/10.1021/acsami.3c00417.
Y. Chen, Y. Huang, J. Zeng, et al., “Energy‐Efficient ReS2‐Based Optoelectronic Synapse for 3D Object Reconstruction and Recognition,” ACS Applied Materials & Interfaces 15, no. 50 (2023): 58631–58642, https://doi.org/10.1021/acsami.3c14958.
M. Huang, W. Ali, L. Yang, et al., “Multifunctional Optoelectronic Synapses Based on Arrayed MoS2 Monolayers Emulating Human Association Memory,” Advanced Science 10, no. 16 (2023): 2300120, https://doi.org/10.1002/advs.202300120.
A. Sharma, T. D. Senguttuvan, V. N. Ojha, and S. Husale, “Novel Synthesis of Topological Insulator Based Nanostructures (Bi2 Te3) Demonstrating High Performance Photodetection,” Sci Rep 9, no. 1 (2019): 1–8, https://doi.org/10.1038/s41598‐019‐40394‐z.
W. Wu, W. He, D. Ling, et al., “Enhanced Self‐Powered Photoresponse of a Bi2 Te3 ‐Based Vertical Heterojunction Broadband Photodetector by Carrier Blocking Layer Engineering,” Small 21, no. 29 (2025): 2501484, https://doi.org/10.1002/smll.202501484.
S. Nandi, S. Ghosal, M. Meyyappan, and P. K. Giri, “Defect‐Engineered 2D Bi2Se3‐Based Broadband Optoelectronic Synapses With Ultralow Energy Consumption for Neuromorphic Computing,” Materials Horizons 12, no. 12 (2025): 4274–4288, https://doi.org/10.1039/d4mh01625d.
X. Qi, J. Zhang, J. Cai, X. Chu, X. Shao, and Z. L. Hou, “Delicate Construction of Bi2Te3 Nanosheets for Striking Artificial Synapses and Broadband Photodetecting,” Journal of Alloys and Compounds 1002 (2024): 175350, https://doi.org/10.1016/j.jallcom.2024.175350.
Z. Wan, Q. Zhang, F. Hu, et al., “Topological Insulator Optoelectronic Synapses for High‐Accuracy Binary Image Recognition using Recurrent Neural Networks,” Advanced Optical Materials 11, no. 2 (2023): 2201852, https://doi.org/10.1002/adom.202201852.
Y. Zhang, Q. You, W. Huang, et al., “Few‐Layer Hexagonal Bismuth Telluride (Bi2Te3) Nanoplates With High‐Performance UV–vis Photodetection,” Nanoscale Advances 2, no. 3 (2020): 1333–1339, https://doi.org/10.1039/d0na00006j.
C. Lu, M. Luo, W. Dong, et al., “Bi2 Te3 /Bi2 Se3 /Bi2 S3 Cascade Heterostructure for Fast‐Response and High‐Photoresponsivity Photodetector and High‐Efficiency Water Splitting With a Small Bias Voltage,” Advanced Science 10, no. 6 (2023): 2205460, https://doi.org/10.1002/advs.202205460.
Y. Zhang, W. He, D. Wang, et al., “High‐Performance Self‐Powered UV‐to‐NIR Imaging Photodetector Based on Bi2Te3 p‐n Homojunction,” Materials Today Physics 56 (2025): 101779, https://doi.org/10.1016/j.mtphys.2025.101779.
G. Wang, Q. Li, W. Zhang, et al., “Unveiling the Synergy of Architecture and Anion Vacancy on Bi2 Te3– x @NPCNFs for Fast and Stable Potassium Ion Storage,” ACS Applied Materials & Interfaces 16, no. 11 (2024): 13858–13868, https://doi.org/10.1021/acsami.4c00248.
S. Hu, X. Huang, L. Zhang, et al., “Vacancy‐Defect Topological Insulators Bi2 Te3−x Embedded in N and B Co‐Doped 1D Carbon Nanorods Using Ionic Liquid Dopants for Kinetics‐Enhanced Li–S Batteries,” Advanced Functional Materials 33, no. 20 (2023): 2214161, https://doi.org/10.1002/adfm.202214161.
C. Wang, X. Zhu, L. Nilsson, et al., “In Situ Raman Spectroscopy of Topological Insulator Bi2Te3 Films With Varying Thickness,” Nano Research 6, no. 9 (2013): 688–692, https://doi.org/10.1007/s12274‐013‐0344‐4.
V. Chis, I. Y. Sklyadneva, K. A. Kokh, V. A. Volodin, O. E. Tereshchenko, and E. V. Chulkov, “Vibrations in Binary and Ternary Topological Insulators: First‐Principles Calculations and Raman Spectroscopy Measurements,” Physical Review B—Condensed Matter Material Physics 86, no. 17 (2012): 1–12, https://doi.org/10.1103/PhysRevB.86.174304.
G. Ye, Y. Gong, J. Lin, et al., “Defects Engineered Monolayer MoS2 for Improved Hydrogen Evolution Reaction,” Nano Letters 16, no. 2 (2016): 1097–1103, https://doi.org/10.1021/acs.nanolett.5b04331.
K. Jeong, D. Park, I. Maeng, et al., “Modulation of Optoelectronic Properties of the Bi2Te3 Nanowire by Controlling the Formation of Selective Surface Oxidation,” Appl Surf Sci 548 (2021): 149069, https://doi.org/10.1016/j.apsusc.2021.149069.
R. Galceran, F. Bonell, L. Camosi, et al., “Passivation of Bi2 Te3 Topological Insulator by Transferred CVD‐Graphene: Toward Intermixing‐Free Interfaces,” Advanced Materials Interfaces 9, no. 36 (2022): 2201997, https://doi.org/10.1002/admi.202201997.
A. G. Shard, “Practical Guides for X‐Ray Photoelectron Spectroscopy: Quantitative XPS,” Journal of Vacuum Science & Technology A 38, no. 4 (2020): 41201, https://doi.org/10.1116/1.5141395.
J. F. Moulder, W. F. Stickle, W. M. Sobol, and K. D. Bomben Handbook of X‐Ray Photoelectron Spectroscopy, Physical Electronics Division, Perkin‐Elmer Corporation, Eden Prairie, MN, USA, (1992).
L. Giri, G. Mallick, A. C. Jackson, M. H. Griep, and S. P. Karna, “Synthesis and Characterization of High‐Purity, Single Phase Hexagonal Bi2Te3 Nanostructures,” RSC Advances 5, no. 32 (2015): 24930–24935, https://doi.org/10.1039/c5ra02303c.
R. P. Panmand, G. Kumar, S. M. Mahajan, N. Shroff, B. B. Kale, and S. W. Gosavi, “Growth of Bi2Te3 Quantum Dots/Rods in Glass: A Unique Highly Stable Nanosystem With Novel Functionality for High Performance Magneto Optical Devices,” Physical Chemistry Chemical Physics 14, no. 47 (2012): 16236, https://doi.org/10.1039/c2cp43169f.
B. Sreelakshmi and R. Thamankar, “Investigation of the Transient Photo‐Response and Switching Window of an Al/Indigo/Al Device: Unveiling Negative Photoconductivity and the Photo‐Enhanced Memory Window,” Materials Advance 5, no. 14 (2024): 5912–5921, https://doi.org/10.1039/d4ma00302k.
P. Ci, X. Tian, J. Kang, et al., “Chemical Trends of Deep Levels in Van Der Waals Semiconductors,” Nat Commun 11, no. 1 (2020): 1–8, https://doi.org/10.1038/s41467‐020‐19247‐1.
J. Jiang, C. Ling, T. Xu, et al., “Defect Engineering for Modulating the Trap States in 2D Photoconductors,” Advanced Materials 30, no. 40 (2018): 1804332, https://doi.org/10.1002/adma.201804332.
T. Chen, X. Wang, D. Hao, et al., “Photonic Synapses With Ultra‐Low Energy Consumption Based on Vertical Organic Field‐Effect Transistors,” Advanced Optical Materials 9, no. 8 (2021): 2002030, https://doi.org/10.1002/adom.202002030.
S. E. Ng, J. Yang, R. A. John, and N. Mathews, “Adaptive Latent Inhibition in Associatively Responsive Optoelectronic Synapse,” Advanced Functional Materials 31, no. 28 (2021): 2100807, https://doi.org/10.1002/adfm.202100807.
J. Jiang, W. Xu, Z. Sun, et al., “Wavelength‐Controlled Photoconductance Polarity Switching via Harnessing Defects in Doped PdSe2 for Artificial Synaptic Features,” Small 20, no. 13 (2024): 2306068, https://doi.org/10.1002/smll.202306068.
R. C. Atkinson and R. M. Shiffrin, “Human Memory: A Proposed System and Its Control Processes,” Psychology of Learning and Motivation, Academic Press 2 (1968): 89–195, https://doi.org/10.1016/S0079‐7421(08)60422‐3.
AT&T Laboratories Cambridge ORL Face Database available, https://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html 2009.
P. Zhao, X. Peng, M. Cui, et al., “Multifunctional Two‐Terminal Optoelectronic Synapse Based on an Organic Semiconductor Film,” ACS Applied Polymer Materials 5, no. 10 (2023): 8764–8773, https://doi.org/10.1021/acsapm.3c02012.
M. Cordts, M. Omran, S. Ramos, et al., “The Cityscapes Dataset for Semantic Urban Scene Understanding,” Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit 2016 (2016): 3213–3223, https://doi.org/10.1109/CVPR.2016.350.
J. Wu, W. Liu, C. Li, et al., “A State‐of‐the‐Art Survey of U‐Net in Microscopic Image Analysis: From Simple Usage to Structure Mortification,” Neural Computing and Applications 36, no. 7 (2023): 3317–3346, https://doi.org/10.1007/s00521‐023‐09284‐4.
R. G. Parr, “Density Functional Theory,” Annual Review of Physical Chemistry 34 (1983): 631–656, https://doi.org/10.1146/annurev.pc.34.100183.003215.
P. Giannozzi, S. Baroni, N. Bonini, et al., “QUANTUM ESPRESSO: A Modular and Open‐Source Software Project for Quantum Simulations of Materials,” Journal of Physics: Condensed Matter 21, no. 39 (2009): 395502, https://doi.org/10.1088/0953‐8984/21/39/395502.
P. E. Blöchl, “Projector Augmented‐Wave Method,” Phys Rev B 50, no. 24 (1994): 17953–17979, https://doi.org/10.1103/PhysRevB.50.17953.
J. P. Perdew, K. Burke, and M. Ernzerhof, “Generalized Gradient Approximation Made Simple,” Physical Review Letters 77, no. 18 (1996): 3865–3868, https://doi.org/10.1103/PhysRevLett.77.3865.
Grant Information:
5(1)/2022-NANO MEITY
Contributed Indexing:
Keywords: 2D Bi2Te3; defect engineering; facial recognition; logic gates; optoelectronic synapse; topological insulator; ultralow energy consumption
Entry Date(s):
Date Created: 20260123 Latest Revision: 20260123
Update Code:
20260123
DOI:
10.1002/smll.202511836
PMID:
41574840
Database:
MEDLINE
Weitere Informationen
Advances in optoelectronic synapses (OES) have relied on complex device configurations and fabrication processes, which limit their practical implementation. Here, we exploit the untapped potential of ultrathin Bi <subscript>2</subscript> Te <subscript>3</subscript> to construct a multifunctional OES device for a range of applications in neuromorphic computing, biometric recognition, and artificial visual perception. The Te vacancies in the film trap and de-trap charges, leading to persistent photoconductivity as the operating mechanism. Specifically, we demonstrate successful defect engineering by controlling the annealing temperature of the Bi <subscript>2</subscript> Te <subscript>3</subscript> films and directly correlate the OES performance with the defect density. The role of the Te vacancies in OES is further confirmed by first-principles calculations. The OES devices show excellent metrics such as 191.7% paired-pulse facilitation and 37.2 fJ per spike of energy consumption. The device successfully simulates Pavlov's classic associative learning experiment. A 6 × 6 device array, serving as an artificial retina for image processing, displays excellent retention of the learned optical information and memory performance by 57.4%. The OES devices demonstrate high accuracy in facial recognition (93.3%) and urban traffic scene segmentation (86.7%) tasks after 100 epochs. Finally, successful optical logic gate operations and Morse code for optical signal recognition and wireless communication are demonstrated using the OES devices.
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